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[Multiple observations] Addresses issue #571 #573

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Apr 6, 2018
Merged

[Multiple observations] Addresses issue #571 #573

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7 changes: 4 additions & 3 deletions python/unitytrainers/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,15 +80,16 @@ def create_continuous_state_encoder(self, h_size, activation, num_layers):
kernel_initializer=c_layers.variance_scaling_initializer(1.0))
return hidden

def create_visual_encoder(self, h_size, activation, num_layers):
def create_visual_encoder(self, image_input, h_size, activation, num_layers):
"""
Builds a set of visual (CNN) encoders.
:param image_input: The placeholder for the image input to use.
:param h_size: Hidden layer size.
:param activation: What type of activation function to use for layers.
:param num_layers: number of hidden layers to create.
:return: List of hidden layer tensors.
"""
conv1 = tf.layers.conv2d(self.visual_in[-1], 16, kernel_size=[8, 8], strides=[4, 4],
conv1 = tf.layers.conv2d(image_input, 16, kernel_size=[8, 8], strides=[4, 4],
activation=tf.nn.elu)
conv2 = tf.layers.conv2d(conv1, 32, kernel_size=[4, 4], strides=[2, 2],
activation=tf.nn.elu)
Expand Down Expand Up @@ -136,7 +137,7 @@ def create_new_obs(self, num_streams, h_size, num_layers):
hidden_state, hidden_visual = None, None
if brain.number_visual_observations > 0:
for j in range(brain.number_visual_observations):
encoded_visual = self.create_visual_encoder(h_size, activation_fn, num_layers)
encoded_visual = self.create_visual_encoder(self.visual_in[j], h_size, activation_fn, num_layers)
visual_encoders.append(encoded_visual)
hidden_visual = tf.concat(visual_encoders, axis=1)
if brain.vector_observation_space_size > 0:
Expand Down